425 programming-language-"St"-"University-of-St"-"St" PhD positions in United Kingdom
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intellectually to other projects developed in the Laboratory. Excellent oral and written English. Funding This four-year studentship will cover University fees and an index-linked stipend starting at £22,113
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Location: UK Other Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives
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or carried out their main activity in the UK formore than 12 months in the 36 months before the recruitment date. Must hold a Master’s degree by the start date (September 2025). Good English proficiency
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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Rolls-Royce University Technology Centre (UTC) in manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership
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degree or higher) • UK home student status holder • Excellent oral and written communication skills in English • Strong problem-solving abilities • Interdisciplinary data science and energy interests
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deadline passes. You will need to meet the minimum entry requirements for our PhD programme . Candidates should have a strong background and first degree in chemistry or closely related subject (BSc/MChem
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be possible, please contact Professor Chris Proudman once deadline passes. You will need to meet the minimum entry requirements for our PhD programme . Additional requirements: Familiarity with horses
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Excellent oral and written communication skills in English Strong problem-solving abilities Interdisciplinary computer science interests Ability to work independently and in a collaborative environment
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins